Learning From Data

Learning from Data focuses on how to interpret psychological data and statistical results. The authors review the basics of statistical reasoning to helpstudents better understand relevant data that affecttheir everyday lives.

Numerous examples based on current research and events are featured throughout.To facilitate learning, authors Glenberg and Andrzejewski:

• Devote extra attention to explaining the more difficult concepts and the logic behind them
• Use repetition to enhance students’ memories with multiple examples, reintroductions of the major concepts, and a focus on these concepts in the problems
• Employ a six-step procedure for describing all statistical tests from the simplest to the most complex
• Provide end-of-chapter tables to summarize the hypothesis testing procedures introduced
• Emphasizes how to choose the best procedure in the examples, problems and endpapers
• Focus on power with a separate chapter and power analyses procedures in each chapter
• Provide detailed explanations of factorial designs, interactions, and ANOVA to help students understand the statistics used in professional journal articles.

The third edition has a user-friendly approach:

• Designed to be used seamlessly with Excel, all of the in-text analyses are conducted in Excel, while the book’s downloadable resources contain files for conducting analyses in Excel, as well as text files that can be analyzed in SPSS, SAS, and Systat
• Two large, real data sets integrated throughout illustrate important concepts
• Many new end-of-chapter problems (definitions, computational, and reasoning) and many more on the companion CD
• Online Instructor’s Resources includes answers to all the exercises in the book and multiple-choice test questions with answers
• Boxed media reports illustrate key concepts and their relevance to realworld issues
• The inclusion of effect size in all discussions of power accurately reflects the contemporary issues of power, effect size, and significance.

Learning From Data, Third Edition is intended as a text for undergraduate or beginning graduate statistics courses in psychology, education, and other applied social and health sciences.